How Levi Strauss is using AI for its DTC-first business model
In its pursuit of a direct-to-consumer (DTC) first business model, Levi Strauss is weaving AI and cloud platforms into its core operations.
The almost 175-year-old attire firm is leveraging Microsoft applied sciences to modernise its client experiences and enhance inside productiveness. Levi Strauss’ method gives a case examine for different enterprises in using a unified know-how stack to handle a selected business goal.
AI ‘superagent’: A unified front-end for operations at Levi Strauss
A central part of this initiative is the event of agentic AI options. Levi Strauss is deploying an Azure-native “orchestrator agent” embedded inside Microsoft Teams, which features as a “superagent”.
This agent serves as a single conversational portal for staff throughout company, retail, and warehouse environments. Operationally, it fields worker questions and routes them to specialist behind-the-scenes subagents, a few of that are already deployed. This factors towards a consolidation of employee-facing instruments; as an alternative of coaching workers on a number of purposes, the agent gives a single interface to streamline workflows.
This AI-centric business model is a part of a wider objective outlined by Jason Gowans, Chief Digital and Technology Officer at Levi Strauss & Co.
“We’re rewiring Levi Strauss & Co to be a DTC-first, fan-obsessed retailer making each interplay quicker, smarter, and extra private,” mentioned Gowans. “AI sits on the heart of that pivot—fueling innovation, elevating worker creativity, unlocking productiveness, and serving to us ship the related, memorable experiences that preserve our followers returning many times.”
This deal with productiveness extends to the developer facet. Teams are using GitHub Copilot for key tasks involving high quality engineering and launch administration. At the identical time, different staff are being outfitted with Microsoft Surface Copilot+ PCs. Employee suggestions signifies these units have led to enhancements in pace and knowledge dealing with, with options just like the Copilot key decreasing time spent looking out for info.
The foundational cloud and safety posture
Levi Strauss’ AI implementation rests on prerequisite infrastructure work. For business leaders, this highlights that superior AI fashions require a consolidated cloud setting.
As a part of its broader digital efforts, Levi Strauss is counting on Microsoft Azure, having moved utility workloads from its on-premises knowledge centres. The firm used Azure Migrate and GitHub Copilot to plan and execute the consolidation of its personal knowledge centre setting.
This cloud basis is additionally central to the corporate’s safety posture. Levi Strauss is leveraging Azure AI Foundry and Semantic Kernel to construct clever automation capabilities.
Security is being built-in into the AI framework itself and the instruments are getting used to energy safety brokers and coverage orchestration; a way that permits Levi Strauss to take care of a zero-trust safety model whereas persevering with to scale its AI-driven initiatives throughout world operations.
To handle the brand new {hardware} endpoints, the corporate is additionally using Microsoft Intune for zero-touch system onboarding and utility deployment.
Leveraging the total AI ecosystem to pivot business model
Levi Strauss’ initiative demonstrates an ecosystem-based method to adopting AI. Rather than a piecemeal rollout of particular person instruments, the corporate is integrating AI brokers, developer instruments, and new {hardware} on high of a typical cloud platform.
Keith Mercier, VP of Worldwide Retail and Consumer Goods Industry at Microsoft, famous that Levi Strauss “exemplifies how iconic manufacturers can reinvent themselves with cloud and AI applied sciences.”
For different enterprises, the Levi Strauss case examine serves as a blueprint for linking AI and foundational cloud migration on to high-value outcomes just like the pivot to a DTC business model.
See additionally: IBM: Data silos are holding back enterprise AI

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